A systematic review of conversational AI in language education: focusing on the collaboration with human teachers

Ji, Hyangeun; Han, Insook; Ko, Yujung

doi:10.1080/15391523.2022.2142873

Cited by 80 publications

(31 citation statements)

References 58 publications

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“…In a recent review on conversational AI in language education, the authors found that there are five main applications of conversational AI during teaching [22], the most common one being the use of large language models as a conversational partner in a written or oral form, e.g., in the context of a task-oriented dialogue that provides language practice opportunities such as pronunciation [23]. Another application is to support students when they experience foreign language learning anxiety [24] or have a lower willingness to communicate [25].…”

Section: Review Of Research Applying Large Languagementioning

confidence: 99%

ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education

Kasneci¹,

Seßler²,

Küchemann³

et al. 2023

Preprint

120

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Large language models represent a significant advancement in the field of AI. The underlying technology is key to further innovations and, despite critical views and even bans within communities and regions, large language models are here to stay. This position paper presents the potential benefits and challenges of educational applications of large language models, from student and teacher perspectives. We briefly discuss the current state of large language models and their applications. We then highlight how these models can be used to create educational content, improve student engagement and interaction, and personalize learning experiences. With regard to challenges, we argue that large language models in education require teachers and learners to develop sets of competencies and literacies necessary to both understand the technology as well as their limitations and unexpected brittleness of such systems. In addition, a clear strategy within educational systems and a clear pedagogical approach with a strong focus on critical thinking and strategies for fact checking are required to integrate and take full advantage of large language models in learning settings and teaching curricula. Other challenges such as the potential bias in the output, the need for continuous human oversight, and the potential for misuse are not unique to the application of AI in education. But we believe that, if handled sensibly, these challenges can offer insights and opportunities in education scenarios to acquaint students early on with potential societal biases, criticalities, and risks of AI applications. We conclude with recommendations for how to address these challenges and ensure that such models are used in a responsible and ethical manner in education.

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Section: Review Of Research Applying Large Languagementioning

confidence: 99%

ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education

Kasneci¹,

Seßler²,

Küchemann³

et al. 2023

Preprint

120

View full text Add to dashboard Cite

show abstract

“…For instance, LLMs have been used to generate children's narratives [4,35], some of which have even been sold publicly [64]. In a different research trajectory, several scholars have used LLMs to create intelligent learning partners capable of collaborating with humans [47], providing feedback [49] and encouraging students [24,88]. One common application involves employing LLMs as a conversational partner in written or oral form, such as in the context of task-oriented dialogues that offer language practice opportunities [24].…”

Section: Using Large Language Models For Child-facing Conversational ...mentioning

confidence: 99%

Mathemyths: Leveraging Large Language Models to Teach Mathematical Language through Child-AI Co-Creative Storytelling

Zhang,

Liu,

Ziska

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Figure 1: Interaction between a child and Mathemyths: demonstrating the system's ability to teach mathematical language through child-AI co-creative storytelling. Mathemyths provides open-ended questions to solicit how the child wishes the story should progress, on-the-fly feedback to acknowledge the child's responses, and co-creative story continuation with in-context explanations of math words. When the child needs additional support to continue the story, Mathemyths offers scaffolding through follow-up questions and "hint & rephrase" strategies.

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“…The adoption of large language models (LLMs), such as GPT-3 and newer iterations, in educational settings has been increasing, transforming ways of teaching and learning [39,40]. The integration of LLMs into educational practices leverages the capability of these models to simulate complex human interactions, providing students with a unique platform for practicing communication strategies in a controlled environment [41,42].…”

Section: Llms In Educationmentioning

confidence: 99%

Teamwork Conflict Management Training and Conflict Resolution Practice via Large Language Models

Aggrawal,

Magana

2024

Future Internet

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This study implements a conflict management training approach guided by principles of transformative learning and conflict management practice simulated via an LLM. Transformative learning is more effective when learners are engaged mentally and behaviorally in learning experiences. Correspondingly, the conflict management training approach involved a three-step procedure consisting of a learning phase, a practice phase enabled by an LLM, and a reflection phase. Fifty-six students enrolled in a systems development course were exposed to the transformative learning approach to conflict management so they would be better prepared to address any potential conflicts within their teams as they approached a semester-long software development project. The study investigated the following: (1) How did the training and practice affect students’ level of confidence in addressing conflict? (2) Which conflict management styles did students use in the simulated practice? (3) Which strategies did students employ when engaging with the simulated conflict? The findings indicate that: (1) 65% of the students significantly increased in confidence in managing conflict by demonstrating collaborative, compromising, and accommodative approaches; (2) 26% of the students slightly increased in confidence by implementing collaborative and accommodative approaches; and (3) 9% of the students did not increase in confidence, as they were already confident in applying collaborative approaches. The three most frequently used strategies for managing conflict were identifying the root cause of the problem, actively listening, and being specific and objective in explaining their concerns.

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A systematic review of conversational AI in language education: focusing on the collaboration with human teachers

Cited by 80 publications

References 58 publications

ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education

ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education

Mathemyths: Leveraging Large Language Models to Teach Mathematical Language through Child-AI Co-Creative Storytelling

Teamwork Conflict Management Training and Conflict Resolution Practice via Large Language Models

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